Associate Process Manager

Role & Responsibilities

• Analyze business and customer datasets to identify trends, patterns, opportunities, and key performance drivers.
• Develop, maintain, and enhance interactive dashboards and reports using Power BI and/or Tableau.
• Translate business requirements into meaningful KPIs, analytical solutions, dashboards, and reporting frameworks.
• Perform ad-hoc analysis, data deep dives, and root-cause analysis to support business decision-making.
• Prepare clear and actionable insights using effective data visualization and storytelling techniques.
• Validate data accuracy, consistency, and completeness across reports and analytical outputs.
• Collaborate with business, technology, and data teams to understand requirements and deliver analytical solutions.
• Document KPI definitions, analytical methodologies, assumptions, and reporting logic to ensure consistency and reuse.

Must Have Skills

• Strong proficiency in SQL, including joins, CTEs, aggregations, subqueries, and window functions.
• Strong hands-on experience with Power BI and/or Tableau for dashboard development and data visualization.
• Strong Excel skills, including advanced formulas, pivot tables, lookups, and data analysis.
• Strong analytical and problem-solving skills with the ability to investigate and interpret complex datasets.
• Ability to translate business requirements into measurable KPIs, reports, and analytical solutions.
• Good understanding of data quality, validation, and basic data modeling concepts.
• Ability to communicate analytical findings clearly to technical and non-technical stakeholders.

Good to Have

• Python/Pandas for data analysis, automation, and data preparation.
• Experience with cloud data platforms such as Snowflake, BigQuery, Databricks, Azure, or AWS.
• Understanding of statistical concepts such as hypothesis testing, correlation, regression, A/B testing, and confidence intervals.
• Experience with Git/GitHub or other version-control tools.
• Experience working with large-scale datasets and analytical data models.

AI / GenAI

• Experience using Generative AI / LLM tools for data exploration, SQL generation, analysis, documentation, or workflow automation.
• Familiarity with prompt engineering and responsible use of AI in analytics.
• Exposure to AI-assisted BI, natural-language analytics, or automated insight generation.